11 dépôts
Software distributed and managed via the Python Package Index and associated tools.
Explore 11 awesome GitHub repositories matching development tools & productivity · Python Packages. Refine with filters or upvote what's useful.
This project is a command-line media downloader designed for the systematic retrieval and organization of digital content from diverse online platforms. It functions as an extensible extraction engine that utilizes a declarative format-selection pipeline to automate the identification, merging, and downloading of specific audio and video streams based on user-defined criteria. The system distinguishes itself through a modular architecture that supports custom plugins and site-specific scripts, allowing for the bypass of platform restrictions and the handling of complex authentication challeng
Supports installation and dependency resolution through standard Python package management workflows.
Python is a high-level, interpreted programming language designed for readability and versatility. It operates via a bytecode-based virtual machine and manages memory automatically through reference-counting garbage collection. The language supports multiple programming paradigms, including object-oriented, imperative, and functional styles, and provides a comprehensive standard library for system operations, networking, and data handling. The language is distinguished by its dynamic nature, allowing for runtime object introspection and metaclass-driven class creation. It utilizes protocol-ba
Provides a central repository for distributing and installing third-party software packages.
This project is a cross-platform machine learning inference engine designed to execute pre-trained models across diverse operating systems and hardware environments. It functions as a standardized execution framework that manages the entire lifecycle of model inference, from loading and graph optimization to hardware-accelerated execution and generative sequence management. The runtime distinguishes itself through a highly modular architecture that decouples model logic from hardware-specific kernels. By utilizing an execution provider abstraction, it enables developers to offload computation
Bundles specialized machine learning operations into installable packages for Python, Java, and other environments.
Gitingest is a Git repository analysis and conversion service that transforms code repositories into structured plain-text summaries optimized for large language model consumption. It provides HTTP API endpoints and Python functions to integrate repository processing into AI pipelines and applications, with S3-compatible storage for persisting and retrieving generated digests. The service is packaged as a Docker container with all dependencies bundled for consistent deployment across environments. The project distinguishes itself through asynchronous processing of multiple repositories concur
Provides HTTP endpoints and Python functions to consume repository digests in AI pipelines and applications.
pip-tools is a set of utilities for Python dependency pinning, lockfile management, and virtual environment synchronization. It functions as a requirement compiler that resolves high-level package declarations into a pinned list of specific versions and content hashes to ensure repeatable builds across different environments. The tool differentiates itself by providing a mechanism to refresh locked dependencies to their latest compatible versions without manual editing. It supports a layered dependency workflow, allowing one requirements file to act as a constraint for another to maintain com
Generates pinned requirements files with hashes to ensure installations use identical package versions and checksums.
Ce projet fournit une collection de guides de référence PDF et de résumés visuels pour la bibliothèque de traçage Matplotlib. Ces guides de visualisation de données combinent des exemples de code et des aides visuelles pour produire une documentation technique condensée et des fiches mémo (cheat sheets). La documentation est produite via un pipeline de compilation basé sur LaTeX. Ce système transforme le code source structuré en PDF formatés de haute qualité en utilisant un moteur de mise en page multi-colonnes et une génération d'assets pilotée par script pour les figures. Le processus de build inclut un pipeline d'assets automatisé qui gère la résolution des dépendances de police et valide les fichiers générés pour le nombre de pages et l'intégrité des liens.
Creates quick-reference PDF guides that combine code examples and visual aids for faster Matplotlib library usage.
pipreqs est un générateur de dépendances Python et un outil de découverte. Il scanne les imports du projet pour identifier les bibliothèques tierces nécessaires à l'exécution d'un projet et automatise la génération de fichiers requirements contenant uniquement les paquets réellement utilisés dans le code source. L'utilitaire fonctionne comme un gestionnaire de fichiers requirements en comparant les paquets installés avec les imports réels. Il fournit des capacités pour élaguer les dépendances inutilisées et auditer les projets afin d'identifier les paquets manquants ou obsolètes. L'outil emploie l'analyse statique et les arbres de syntaxe abstraite pour isoler les instructions d'importation sans exécuter le code. Il résout les versions des paquets en utilisant des métadonnées locales ou des serveurs personnalisés et traverse récursivement les structures de répertoires pour localiser tous les fichiers sources pertinents.
Identifies specific third-party libraries required to run a project based on its import statements.
Feast is an open-source feature store for machine learning that provides a central platform for defining, storing, and serving features across both training and inference workflows. It operates as a declarative system where feature definitions are written as code in Python files, synchronized to a central registry, and made available for low-latency online retrieval or point-in-time correct historical joins for training datasets. The project abstracts storage behind a pluggable architecture, allowing offline and online backends to be swapped without changing retrieval logic, and coordinates ma
Structures shared feature definitions, entities, sources, and transformations into reusable Python packages within a project.
This repository is the source for a curated collection of printable reference sheets for R and Python packages. It provides quick-reference guides organized by topic, available as both PDF files for offline printing and interactive HTML versions for online browsing. The collection also includes community-contributed translations of these reference sheets into multiple languages, expanding accessibility for non-English speakers. The project is built around a reproducible rendering pipeline that generates both PDF and HTML formats from source documents, using a lockfile to guarantee identical b
Provides printable quick-reference guides summarizing key functions for popular Python packages.
Warehouse is a web application designed for hosting, storing, and distributing Python software packages to a global community of users. It functions as a centralized package repository and index server that manages software versions, metadata, and package classification. The project implements secure package attestation by verifying distribution integrity through cryptographic signatures and transparency logs. It manages user identity via an OAuth provider that integrates with third-party identity services using secure tokens. The system covers a broad range of infrastructure capabilities, i
Operates a centralized system for managing Python software distributions and version metadata.
micropython-lib is the official package repository for MicroPython, providing a collection of modules and libraries designed to run on microcontrollers and other constrained devices. It implements a reduced subset of CPython's standard library, adapting familiar Python interfaces to fit within the limited memory and processing power of embedded systems. The project enables developers to reuse existing Python knowledge on MicroPython hardware by offering minimalist implementations of core modules. The library supports multiple methods for getting code onto devices, including copying single-fil
Adapts select third-party Python packages for use in MicroPython, extending functionality beyond the standard library.